Enterprise Data Quality Implementation

Framework for establishing and sustaining high data quality levels. Measure, Monitor, Report, Remediate, Repeat



Define KPI’s and DQ Metrics Define DQ Dimensions Define alerts Define SLA’s


Monitor data quality issues Determine impact of remediation Build and monitor data quality reports Build and monitor data quality trend reports Build “After” state


Analyze anomalies Identify true data issues Perform root cause analysis Prepare plan for remediation Remediate data issues


Identify and collect business DQ rules Separate business rules from technical rules Identify thresholds Define remediation process

Discover and Profile

Establish Business cases Costs of bad data Identify data sources Identify stakeholders Profile data for timeliness, accuracy, completeness, consistency. Memorialize “Before” state

Build & Execute

Identify and evaluate DQ tool options Select tool Design and Build data quality rules Test and Deploy Execute the rules to identify anomalies